I am working on verifying bandwidth consumption for my proposed method with the existing related work. I have verified the same with simulation results and would now also like to verify the results analytically. How can i proceed ahead. Should i have to derive a mathematical expression and then simulate it and compare with the simulation set of results. I lack the understanding of theoretical analysis.
Both analytical and simulation methods are modelling approaches which aim at providing an idea of system performance, in different conditions.
An analytic model is a mathematical abstraction that can be extended to address various working conditions, thanks to some assumptions about the way a process is evolving. In some cases, an exact solution can be derived and a result can be obtained in various conditions. The beauty of the analytical model is that it provides a generic way to get performance results in various conditions through a mathematical formulation. The accuracy of the model is to be considered through the alidity of the assumption to derive the mathematical formulation. Some uncertainties can be handled through a stochastic model to account for modelling and measurement model.
A simulation model such as a monte-carlo also make assumption of a model and some assumption about the behaviour of the process. It is used when an analytical formulation cannot be derived (for example when the size of the model is too large,or when no exact solution can be derived). Simulation models provide results for a specific use case and should be run many times to counterbalance the effect of numerical calculations. For a different functioning use case, the simulation should be run over again. A simulation model can be accepted when results are validated in a number of working conditions under various input assumptions.
When the two approaches can be used, preference should be given to the analytical approach and simultation can be used to validate the assumptions and the models. For better analysis, the simultaion model could be used with assumptions slightly different from the analytical model, since simultation is not aimed at validating the model but the reality of the modelled process.
If you have a mathematical model for your system.Then you have to approach the analytical method for evaluating your simulation results.
Both simulation & analytical results are needed for the best papers. If you put a analytical and mathematical knowledge, your paper become more stronger and acceptable.
From my understanding, we use similations to validate the analytical results derived from mathematical expression of a proposed model or method. We are most interested to see whether both analytical and simulation are well agreed. If both results are well agreed, the analytical model is quite accurate.
It is depend on your work if your work is based on the mathametical model so you should add analytical results and if not so no need directly go with simulation results.
Both analytical and simulation methods are modelling approaches which aim at providing an idea of system performance, in different conditions.
An analytic model is a mathematical abstraction that can be extended to address various working conditions, thanks to some assumptions about the way a process is evolving. In some cases, an exact solution can be derived and a result can be obtained in various conditions. The beauty of the analytical model is that it provides a generic way to get performance results in various conditions through a mathematical formulation. The accuracy of the model is to be considered through the alidity of the assumption to derive the mathematical formulation. Some uncertainties can be handled through a stochastic model to account for modelling and measurement model.
A simulation model such as a monte-carlo also make assumption of a model and some assumption about the behaviour of the process. It is used when an analytical formulation cannot be derived (for example when the size of the model is too large,or when no exact solution can be derived). Simulation models provide results for a specific use case and should be run many times to counterbalance the effect of numerical calculations. For a different functioning use case, the simulation should be run over again. A simulation model can be accepted when results are validated in a number of working conditions under various input assumptions.
When the two approaches can be used, preference should be given to the analytical approach and simultation can be used to validate the assumptions and the models. For better analysis, the simultaion model could be used with assumptions slightly different from the analytical model, since simultation is not aimed at validating the model but the reality of the modelled process.
The mathematical analysis usually makes the practical implementation more easier and open other opportunities for researchers to make further improvements. It also confirm that the obtained results are theoretically valid and more robust. However, the simulation results are also acceptable, but sometimes simulation findings do not give accurate evaluation due to the variation in the simulation environments. Simulation can be an acceptable tool for comparison between two approaches and it greatly depends on the nature of the proposed approach. For most of approach the overlap of the theoretical and simulation results is a clear sign of certitude.
This was my answer on a similar question. Hope it will will clarify the concepts.
I will try to define the terms analytic and simulation within the scope of a specific example. Assume that we have an electronic circuit as a single transistor amplifier circuit and we want to determine its dc node voltages and branch currents knowing the circuit diagram and the electrical properties of the circuit elements.
This problem can be solved analytically by using algebraic equations and this can be accomplished only by linearizing the dc characteristics of the transistor as we all know.
This problem can be solved also by simulating the circuit into a computer where one develops a program to describe the circuit into the computer and model elements by a mathematical expressions describing their real behavior as precise as possible. Then a numerical solver is developed which is able solve the sytem of equations of the circuit. One can study the effect of the circus parameters on its performance
The third method is to go to the laboratory and implement the circuit and measure it voltages and currents. One can also study experimentally the effect of the circuit parameters on the performance of the circuit.
All these methods are analysis method, the first is analytic. the second is numerical and the third is experimental.
The computer program can be developed such that it simulates the laboratory. Think on PSPICE and EWP. These programs act a if you you have a circuit laboratory. They are virtual circuit laboratory. You run experiments without going to the laboratory. This is simulation.
So, this is my understanding for analytic, analysis and simulation.
Thank you
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